Non-Gaussian Wind Pressure on Prismatic Buildings. II: Numerical Simulation

Gioffré, Massimiliano; Gusella, Vittorio; Grigoriu, Mircea

doi:10.1061/(asce)0733-9445(2001)127:9(990)

Cited by 35 publications

(12 citation statements)

References 11 publications

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“…A relatively small number of simulation techniques have been developed so far for non-Gaussian vector (multi-variate) processes and fields [5,70,71,143,147]. These stochastic fields are useful for the representation of spatially correlated system properties or random loads in the stochastic finite element method (see Section 3).…”

Section: The Case Of Non-gaussian Vector Processes and Fieldsmentioning

confidence: 99%

“…The algorithm by Gioffrè et al is based on translation vector processes and thus it is not iterative. Conditions on the cross-covariance matrix are given to assure the applicability of the model, which is calibrated on the basis of experimental results obtained from wind tunnel tests on a tall building [70,71]. The method is efficient for reproducing the non-Gaussian nature of pressure fluctuations on separated flow regions.…”

Section: The Case Of Non-gaussian Vector Processes and Fieldsmentioning

confidence: 99%

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The stochastic finite element method: Past, present and future

Stefanou

2009

Computer Methods in Applied Mechanics and Engineering

862

407

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a b s t r a c tA powerful tool in computational stochastic mechanics is the stochastic finite element method (SFEM). SFEM is an extension of the classical deterministic FE approach to the stochastic framework i.e. to the solution of static and dynamic problems with stochastic mechanical, geometric and/or loading properties. The considerable attention that SFEM received over the last decade can be mainly attributed to the spectacular growth of computing power rendering possible the efficient treatment of large-scale problems. This article aims at providing a state-of-the-art review of past and recent developments in the SFEM area and indicating future directions as well as some open issues to be examined by the computational mechanics community in the future.

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Section: The Case Of Non-gaussian Vector Processes and Fieldsmentioning

confidence: 99%

Section: The Case Of Non-gaussian Vector Processes and Fieldsmentioning

confidence: 99%

The stochastic finite element method: Past, present and future

Stefanou

2009

Computer Methods in Applied Mechanics and Engineering

862

407

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show abstract

“…An extension to flexible buildings is in progress. Added to the software will be an automated procedure, based on results of Gioffr" e et al [9], for interpolation of pressure time histories for buildings with dimensions different from those covered in the database. The software described in [8] has been expanded to include probabilistic modules that provide information on the estimated probability distribution of the peak internal forces for a specified wind speed [10].…”

Section: Article In Pressmentioning

confidence: 99%

Achieving safer and more economical buildings through database-assisted, reliability-based design for wind

Simiu

Sadek

Whalen

et al. 2003

Journal of Wind Engineering and Industrial Aerodynamics

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“…Several methodologies have been applied to model this class of problems [11][12][13][14][15][16]. Most of the work has focused on statisticallybased stochastic simulation methods [11][12][13][14], although neural networks are beginning to be used.…”

Section: Introductionmentioning

confidence: 99%

“…Most of the work has focused on statisticallybased stochastic simulation methods [11][12][13][14], although neural networks are beginning to be used. For example, Fu et al [15] predicted wind-induced pressures on a large gymnasium roof with backpropagation and fuzzy neural networks.…”

Section: Introductionmentioning

confidence: 99%